Discover and Qualify Leads While You Sleep
Text embedding, also known as vectorization, is a technique that converts textual data into numerical vector representations. Each word, phrase, or document is mapped to a unique vector, where similar texts have similar embeddings in the high-dimensional vector space. The key idea is that these numerical embeddings capture the semantic relationships and contexts of the original text, allowing artificial intelligence models to effectively process and reason about language data.
Vectorization is a fundamental process in modern AI and NLP systems. It involves converting text data, which is inherently unstructured and challenging for machines to understand, into numerical vectors or arrays of numbers.
